tester.py
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	import torch
	from torch.autograd import Variable
	import numpy as np
	import sys
	import time

	class tester:

	def __init__(self, test_loader, logger):
	self.dataLoader=test_loader
	self.logger=logger

	def test(self, net):
	net.eval()
	with torch.no_grad():
	self.di=iter(self.dataLoader)
	local_iter=0
	t0=time.time()
	while True:
	try:
	data=next(self.di)
	img, lbl = data
	img, lbl = img.cuda(), lbl.long().cuda()
	img, lbl = img, lbl
	out= net.forward(img)
	self.logger.add(0,out,lbl)
	local_iter+=1
	t1=time.time()
	if t1-t0>3:
	sys.stdout.write('\rTest iter: %8d' % (local_iter))
	t0=t1
	except StopIteration:
	self.logger.logEpoch(net)
	break
	net.train()